There are many uses of graph network analysis, such as analyzing relationships in social networks, cyber threat detection, and identifying the people most likely to buy a product based on shared preferences. Working with graphs is a function of navigating edges and nodes to discover and understand complex relationships and/or optimize paths between linked data in a network. A graph consists of nodes or vertices (representing the entities in the system) that are connected by edges (representing relationships between those entities). Graphs are mathematical structures used to model many types of relationships and processes in physical, biological, social and information systems. In order to understand NetworkX functionality, you first need to understand graphs. NetworkX is a Python package for complex graph network analysis.
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